Field
The invention is related to advanced driver assistant systems and methods (including automated driving) for assisting a driver in driving a vehicle, in particular a method and system that determines an expected risk for a current driving situation.
Description of the Related Art
Over the last years, many manufacturers tried to improve assistant systems of their vehicles. In particular, driver assistance systems that assist the driver in critical driving situations have been developed to mitigate the risk of being involved in an accident. Such systems often have the capability to sense the environment of the vehicle by using sensors that are mounted in a distributed fashion on the vehicle. Since there are a plurality of sensors available in the car it is possible to perceive the environment of the vehicle to a large extent. Based on such environment perception it is then possible to generate an environment representation that includes information about other traffic participants but also information about road structure, buildings and the like. Often it is calculated from such information from the environment of the vehicle a prediction for future movements not only of the ego-vehicle on which the system is mounted but also the movement of other traffic participants. Such prediction for future trajectories of vehicles that are involved in a current traffic situation allows calculation of a future risk, based on an analysis of the trajectories. Such approach is for example explained in DE 10 2012 005 272 A1 or DE 10 2011 106 176 A1.
On the other side, it is also possible to estimate a risk for the ego-vehicle based on physics modelling based risk estimation that uses velocity, mass and collision probabilities of vehicles. Furthermore, the prior art also discloses approaches that generate a risk map and the driver assistant system then calculates a path through this map that avoids points of high risk. The driver is informed about a path or a driving action he has to perform in order to follow such path.
The problem with all these known prior art approaches is that they only take into consideration risk factors that can be derived from the sensed environment in the current driving situation of the vehicle. However, in many cases knowledge already exists on particularly dangerous locations or types of intersection. For improving the driver assistant system it would therefore be desirable to improve risk estimation for a currently encountered traffic situation thereby profiting from accident statistics for example.
This is achieved by the method for assisting a driver of a vehicle in driving the vehicle, the corresponding system, vehicle and computer program product.